Principal Reliability Engineer - EDS

Principal Reliability Engineer (Principal RE) – Enterprise Data Services (EDS). This senior technical role is responsible for the reliability, resilience, availability, and performance of all data platforms, cloud infrastructure, data products, and data pipelines across the enterprise data organization. The Principal RE sets the strategic vision for Reliability Engineering within EDS and leads the definition, implementation, and continuous evolution of RE practices, tooling, automation, observability frameworks, and AIOps/AI‑driven operations. Key Responsibilities Enterprise Reliability Strategy & Leadership – work closely with the AVP, RE & Production Support to define the reliability engineering strategy, establish long‑term roadmaps, target operating models, and architectural patterns; serve as the highest‑level technical escalation point for systemic reliability issues. Platform & Cloud Reliability – architect and evolve highly reliable, performant, and cost‑efficient cloud‑based platforms across AWS and GCP; oversee reliability controls for Snowflake, EMR, Hadoop/Spark, Kubernetes, and data systems; lead creation and enforcement of SLO/SLI frameworks. AI‑Enabled Operations, AIOps & Intelligent Automation – develop and implement AI‑driven automation for anomaly detection, alert correlation, autonomous remediation, and predictive capacity management using LLMs, prompt engineering, and cloud‑native AI services. End‑to‑End Observability & Operational Excellence – architect enterprise‑wide observability frameworks (logging, metrics, tracing, profiling, event pipelines); establish incident response patterns, post‑incident reviews, and continuous improvement processes. Data Pipeline & Data Product Reliability – define RE best practices for modern data products, governed pipelines, streaming systems, and analytics platforms; embed resilience patterns such as idempotency, checkpointing, replayability, and disaster recovery. Engineering Standards, Governance & Cross‑Org Influence – set and enforce standards for IaC, CI/CD, platform automation, reliability frameworks, and runbook quality; mentor Staff/Senior Engineers; represent Reliability Engineering in architectural reviews and executive‑level discussions. Technical Experience 10+ years in data, cloud, platform engineering, site/reliability engineering, or large‑scale distributed systems, with leadership or technology leader experience. Proficiency with data or cloud platforms and architectural patterns for resilience, networking, security, and distributed data infrastructure. Deep experience supporting or engineering Snowflake, EMR, Hadoop/Spark, Data Integration, and cloud‑native data ecosystems. Programming in Python for large‑scale automation, platform tooling, and reliability frameworks. Experience with Infrastructure‑as‑Code (Terraform, CloudFormation) and enterprise CI/CD. Preferred Qualifications Experience in regulated or highly complex enterprise environments (financial services, insurance, healthcare). Senior Staff Engineer, Engineering or Architecture leadership experience. Knowledge of data governance, metadata, lineage systems, and data quality engineering practices. Certifications in AWS, GCP, Kubernetes, or SRE/DevOps frameworks. Background in AI & AIOps: anomaly detection, event correlation, predictive modeling, and automated remediation. Expertise in observability stacks (Prometheus, Grafana, Datadog, Splunk, Dynatrace, OpenTelemetry) and advanced SLI/SLO frameworks. Demonstrated ability to lead technical strategy at scale, influence senior engineering leaders, mentor engineers, and foster engineering excellence. Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I‑983 Training Plan endorsement for this position. The listed annualized base pay range is: $152,800 - $229,200. Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age #J-18808-Ljbffr The Hartford